Software-defined networking (SDN) is an emerging paradigm, which breaks the vertical integration in traditional networks to provide the flexibility to program the network through (logical) centralized network control. SDN has the capability to adapt its network parameters on the fly based on its operating environment. The decoupled structure of SDN serves as a solution for managing the network with more flexibility and ease. In SDN, the centralized cost effective architecture provides network visibility which helps to achieve efficient resource utilization and high performance. Due to the increasingly pervasive existence of smart programmable devices in the network, SDN provides security, energy efficiency, and network virtualization for enhancing the overall network performance. We present various security threats that are resolved by SDN and new threats that arise as a result of SDN implementation. The recent security attacks and countermeasures in SDN are also summarized in the form of tables. We also provide a survey on the different strategies that are implemented to achieve energy efficiency and network security through SDN implementation. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts, challenges, and research trends in this area. With this paper, readers can have a more thorough understanding of SDN architecture, different security attacks and countermeasures, and energy efficiency.

Software Defined Networking Architecture, Security and Energy Efficiency: A Survey

We study a class of noncooperative general topology networks shared by N users. Each user has a given flow which it has to ship from a source to a destination. We consider a class of polynomial link cost functions adopted originally in the context of road traffic modeling, and show that these costs have appealing properties that lead to predictable and efficient network flows. In particular, we show that the Nash equilibrium is unique, and is moreover efficient. These properties make the polynomial cost structure attractive for traffic regulation and link pricing in telecommunication networks. We finally discuss the computation of the equilibrium in the special case of the affine cost structure for a topology of parallel links.

Competitive routing in networks with polynomial costs

Dynamic resource allocation in GMPLS optical networks (DRAGON) defines a research and experimental framework for high-performance networks required by grid computing and e-science applications. The DRAGON project is developing technology and deploying network infrastructure which allows dynamic provisioning of network resources in order to establish deterministic paths in direct response to end-user requests. This includes multidomain provisioning of traffic-engineering paths using a distributed control plane across heterogeneous network technologies while including mechanisms for authentication, authorization, accounting (AAA), and scheduling. A reference implementation of this framework has been instantiated in the Washington, DC area and is being utilized to conduct research and development into the deployment of optical networks technologies toward the satisfaction of very-high-performance science application requirements.

DRAGON: a framework for service provisioning in heterogeneous grid networks

Network equilibrium models that have traditionally been used for transportation planning have penetrated in recent years to other scientific fields. These models have recently been introduced in the telecommunication networks literature, as well as in the field of game theory. Researchers in the latter fields are not always aware of the very rich literature on equilibrium models outside of their application area. On the other hand, researchers that have used network equilibrium models in transportation may not be aware of new application areas of their tools. The aim of this paper is to present some central research issues and tools in network equilibria and pricing that could bring closer the three mentioned research communities.

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Equilibrium, games, and pricing in transportation and telecommunication networks

Today's networks typically handle traffic engineering (eg, tuning the routing-protocol parameters to optimize the flow of traffic) and failure recovery (eg, pre-installed backup paths) independently In this paper, we propose a unified way to balance load efficiently under a wide range of failure scenarios Our architecture supports flexible splitting of traffic over multiple precomputed paths, with efficient path-level failure detection and automatic load balancing over the remaining paths We propose two candidate solutions that differ in how the routers rebalance the load after a failure, leading to a trade-off between router complexity and load-balancing performance We present and solve the optimization problems that compute the configuration state for each router Our experiments with traffic measurements and topology data (including shared risks in the underlying transport network) from a large ISP identify a "sweet spot" that achieves near-optimal load balancing under a variety of failure scenarios, with a relatively small amount of state in the routers We believe that our solution for joint traffic engineering and failure recovery will appeal to Internet Service Providers as well as the operators of data-center networks

Network architecture for joint failure recovery and traffic engineering

Internet traffic engineering using multi-protocol label switching (MPLS)

Internet traffic engineering is concerned with the performance optimization of IP networks. Multiprotocol Label Switching (MPLS) is an important technology that supports the Internet traffic engineering function. This paper considers a network performance optimization problem related to traffic engineering over MPLS. We investigate the use of a dynamic traffic partitioning and assignment methodology to adaptively map ingress traffic into several parallel Label Switched Paths (LSPs) in MPLS based IP networks. We present a stochastic framework for the traffic partitioning problem. Within this framework, a set of parallel edge disjoint LSPs is modeled by parallel queues and a partitioning algorithm is devised for different service classes that is adaptive to the prevailing state of the network. The performance of this approach is illustrated with numerical examples.

Analytical framework for dynamic traffic partitioning in MPLS networks

Exemplary embodiments include methods and systems for monitoring, analyzing, and troubleshooting of control plane dynamics of a network including collect data associated with the one or more probe modules associated with a network, store the data associated with the one or more probe modules, analyze the data associated with the one or more probes modules, and output a result of the analysis of the data associated with the one or more probe modules to one or more user devices.

Method and system for monitoring and analyzing of routing in ip networks

Multiprotocol Label Switching (MPLS) is an emerging Internet technology that facilitates traffic engineering in service provider networks. This paper considers a network performance optimization problem related to traffic engineering over MPLS. We investigate the issue of dynamic partitioning of MPLS ingress traffic into several parallel Label Switched Paths (LSP). Specifically, we present a stochastic framework for the traffic partitioning problem. Within this framework, a set of parallel edge disjoint LSPs is modeled by parallel queues and a partitioning algorithm is devised for different service classes that is adaptive to the prevailing state of the network. The performance of this approach is illustrated by numerical examples.

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Optimal Traffic Partitioning in MPLS Networks

The demand assigned capacity management (DACM) problem in IP over optical (IPO) network aims at devising efficient bandwidth replenishment schedules from the optical domain conditioned upon traffic evolution processes in the IP domain. A replenishment schedule specifies the location, sizing, and sequencing of link capacity expansions to support the growth of Internet traffic demand in the IP network subject to economic considerations. We develop mathematical models to address the DACM problem in IPO networks within a deterministic context based on a class of inventory management replenishment methods. We apply the technique to IPO networks that implement noncapacity adaptive routing in the IP domain and analyze the performance characteristics in terms of minimizing cumulative replenishment cost over an interval of time. This study represents an application of integrated traffic engineering which concerns collaborative decision making targeted towards network performance improvement that takes into consideration traffic demands, control capabilities, and network assets at different levels in the network hierarchy.

Daniel O. Awduche

Papers

Internet traffic engineering using multi-protocol label switching (MPLS)

Analytical framework for dynamic traffic partitioning in MPLS networks

Method and system for monitoring and analyzing of routing in ip networks

Optimal Traffic Partitioning in MPLS Networks

A framework for demand assigned capacity management (DACM) in IP over optical networks